Data report: OKR
1 Preliminaries
Email received from Colin.Wilson@southwark.gov.uk
Database containing the OKR business information from We Made That in November 2019.
The spreadsheet business database contains all the information which was cross checked and forms the basis of the figures in the report.
The data is also available in GIS polygon format but not all the fields are there, however the two can be easily cross referenced by using the key information reference points. We think the issue might have been perhaps with multi occupier buildings not being able to have more than one row of data on each polygon. Ideally we would have the GIS with all of the information in one place, rather than a master spreadsheet and a separate GIS file. WMT were unable to match the data up for us in GIS unfortunately.
You should be able to reference from the business name but in case there are duplicate names, the address and X,Y co-ordinates are also there. You will notice the X and Y coordinates are missing the first two digits (53 and 17) in the GIS table but I wonder if that is to do with co-ordinate set up in GIS.
2 Load data
2.1 Excel file
From file REDACTED_164_OKR Survey_WMT 2019 business base_191104.xlsx in WMT OKR Business Survey 2019.zip as bbase
2.1.1 Check variables in bbase (47 variables)
## tibble [943 × 47] (S3: tbl_df/tbl/data.frame)
## $ Source...1 : chr [1:943] "2019" "2019" "2019" "2019" ...
## $ Business count : num [1:943] 1 1 1 1 1 1 1 1 1 1 ...
## $ Business within MOB : chr [1:943] "I" "I" NA NA ...
## $ Multiple buildings : chr [1:943] NA NA NA NA ...
## $ Multi-occupier building : chr [1:943] NA NA NA NA ...
## $ Source...6 : chr [1:943] NA NA "152" NA ...
## $ codex : chr [1:943] "MOB" "MOB" "9" "2052" ...
## $ Join : num [1:943] NA NA 713 0 0 335 337 338 727 339 ...
## $ Xcoord : chr [1:943] "MOB" "MOB" "534846.803700000047684" "535173.403300000005402" ...
## $ Ycoord : chr [1:943] "MOB" "MOB" "178091.482300000003306" "178624.803699999989476" ...
## $ AAP : chr [1:943] "Y" "Y" "Y" "N" ...
## $ Site allocation : chr [1:943] "OKR18" "OKR18" "OKR13" "-" ...
## $ Sub-area : chr [1:943] "4" "4" "3" "-" ...
## $ Business name : chr [1:943] "1666 Fire" "31 Media" "3rd Rail" "5 star Salon" ...
## $ Street no : chr [1:943] NA NA "52-56" NA ...
## $ Unit : chr [1:943] NA NA NA NA ...
## $ Floor : chr [1:943] NA NA "0" "0" ...
## $ Street : chr [1:943] "Daisy Business Park" "Daisy Business Park" "Verney Road" "Rotherhithe New Road" ...
## $ 2015-2019 : chr [1:943] "New" "Remained" "New" "Remained" ...
## $ Notes_on_C : chr [1:943] NA NA NA NA ...
## $ Business activity : chr [1:943] "Technical services" "Marketing, Print and Digital / 2015 Decription: Marketing, Print and Digital" "Screen printing" NA ...
## $ SIC CODE : chr [1:943] "749" "181" "181" NA ...
## $ Sector : chr [1:943] "M Services: professional" "D Printing and publishing" "D Printing and publishing" "O Retail" ...
## $ Building use category : chr [1:943] NA NA "Employment" NA ...
## $ Building type : chr [1:943] "3_Pre-1945 factory, depot, or warehouse" "3_Pre-1945 factory, depot, or warehouse" "2_Post-1945 industrial building" "5_Small retail space" ...
## $ Actual number of employee : num [1:943] NA NA 9 2 31 0 5 0 3 0 ...
## $ Estimated number of employee : num [1:943] 4 5 0 0 0 5 0 5 0 4 ...
## $ TOTAL NUMBER OF EMPLOYEE : num [1:943] 4 5 9 2 31 5 5 5 3 4 ...
## $ employees for density : num [1:943] NA NA 9 2 31 5 5 5 3 4 ...
## $ GF multiplier : chr [1:943] NA NA "1" "1" ...
## $ UF multiplier : chr [1:943] NA NA "0.3" "0" ...
## $ B multiplier : chr [1:943] NA NA "0" "0" ...
## $ Long_surve : chr [1:943] NA NA "N" "N" ...
## $ GF Floorspace area : chr [1:943] NA NA "302.5" "56.967498779296797" ...
## $ UF Floorspace : chr [1:943] NA NA "90.75" "0" ...
## $ Total floorspace : chr [1:943] NA NA "393.25" "56.967498779296797" ...
## $ Total floorspace post VOA+15% analysis : chr [1:943] NA NA "415.05" "56.967498779296797" ...
## $ density : num [1:943] NA NA 43.7 28.5 33.9 ...
## $ 2.07 What % of employees of employees live locally? : chr [1:943] NA NA NA NA ...
## $ ...40 : num [1:943] NA NA NA NA NA NA NA NA NA NA ...
## $ ...41 : chr [1:943] NA NA NA NA ...
## $ ...42 : chr [1:943] NA NA NA NA ...
## $ ...43 : chr [1:943] NA NA NA NA ...
## $ ...44 : num [1:943] NA NA NA NA NA NA NA NA NA NA ...
## $ ...45 : num [1:943] NA NA NA NA NA NA NA NA NA NA ...
## $ ...46 : num [1:943] NA NA NA NA NA NA NA NA NA NA ...
## $ ...47 : num [1:943] NA NA NA NA NA NA NA NA NA NA ...2.1.2 Factor levels per variable describing type
## $`Site allocation`
## [1] "-" "OKR10" "OKR11" "OKR12" "OKR13" "OKR14" "OKR15"
## [8] "OKR16" "OKR17" "OKR18" "OKR2" "OKR3" "OKR4" "OKR6"
## [15] "OKR7" "OKR9" "OKRARCH" "SPIL1" "SPIL2"
##
## $`Sub-area`
## [1] "-" "1" "2" "3" "4" "5"
##
## $`SIC CODE`
## [1] "0"
## [2] "1"
## [3] "101"
## [4] "102"
## [5] "105"
## [6] "107"
## [7] "108"
## [8] "110"
## [9] "141"
## [10] "162"
## [11] "181"
## [12] "2"
## [13] "201"
## [14] "203"
## [15] "222"
## [16] "231"
## [17] "236"
## [18] "237"
## [19] "251"
## [20] "255"
## [21] "256"
## [22] "257"
## [23] "310"
## [24] "321"
## [25] "324"
## [26] "329"
## [27] "331"
## [28] "351"
## [29] "352"
## [30] "382"
## [31] "383"
## [32] "390"
## [33] "4"
## [34] "411"
## [35] "412"
## [36] "421"
## [37] "432"
## [38] "439"
## [39] "449"
## [40] "451"
## [41] "452"
## [42] "453"
## [43] "462"
## [44] "463"
## [45] "464"
## [46] "466"
## [47] "467"
## [48] "469"
## [49] "471"
## [50] "472"
## [51] "473"
## [52] "474"
## [53] "475"
## [54] "476"
## [55] "477"
## [56] "479"
## [57] "493"
## [58] "494"
## [59] "512"
## [60] "521"
## [61] "521.1"
## [62] "531"
## [63] "532"
## [64] "551"
## [65] "561"
## [66] "562"
## [67] "563"
## [68] "581"
## [69] "591"
## [70] "592"
## [71] "612"
## [72] "620"
## [73] "631"
## [74] "639"
## [75] "641"
## [76] "682"
## [77] "683"
## [78] "691"
## [79] "692"
## [80] "711"
## [81] "721"
## [82] "741"
## [83] "742"
## [84] "749"
## [85] "750"
## [86] "771"
## [87] "773"
## [88] "791"
## [89] "811"
## [90] "812"
## [91] "813"
## [92] "829"
## [93] "837"
## [94] "838"
## [95] "842"
## [96] "851"
## [97] "852"
## [98] "853"
## [99] "855"
## [100] "856"
## [101] "862"
## [102] "869"
## [103] "871"
## [104] "872"
## [105] "881"
## [106] "889"
## [107] "900"
## [108] "910"
## [109] "920"
## [110] "931"
## [111] "932"
## [112] "951"
## [113] "952"
## [114] "960"
## [115] "A Manufacture: metals and machinery"
## [116] "B Manufacture: other"
## [117] "D Printing and publishing"
## [118] "E Utilities"
## [119] "H Wholesale: food"
## [120] "J Transport and Storage"
## [121] "K Services: education"
## [122] "L Services: public"
## [123] "O Retail"
## [124] "Q Arts, culture, leisure and sports"
## [125] "R Faith"
## [126] "Vacant"
##
## $Sector
## [1] "A Manufacture: metals and machinery"
## [2] "Atomic Studios London"
## [3] "B Manufacture: food, beverages, and catering"
## [4] "C Manufacture: other"
## [5] "D Printing and publishing"
## [6] "E Utilities"
## [7] "F Vehicle sale and repair"
## [8] "G Construction"
## [9] "H Wholesale: food"
## [10] "H Wholesale: Food"
## [11] "I Wholesale: other"
## [12] "J Transport and storage"
## [13] "J Transport and Storage"
## [14] "K Services: education"
## [15] "L Services: public"
## [16] "M Services: professional"
## [17] "N Services: other"
## [18] "O Retail"
## [19] "P Resteraunts, cafes, takeaways"
## [20] "Q Arts, culture, leisure and sports"
## [21] "R Faith"
## [22] "S Unknown"
## [23] "Vacant"
##
## $`Building use category`
## [1] "Employment"
## [2] "Employment (sui generis - car wash)"
## [3] "Employment (sui generis)"
## [4] "Employment (Vacant)"
## [5] "Leisure, Faith, Education & Health"
## [6] "Leisure, Faith, Education & Health (vacant)"
## [7] "Retail"
## [8] "Retail (Vacant)"
##
## $`Building type`
## [1] "1_Purpose-built industrial shed"
## [2] "10_School"
## [3] "11_Railway arch"
## [4] "13_Other"
## [5] "2_Post-1945 industrial building"
## [6] "3_Pre-1945 factory, depot, or warehouse"
## [7] "4_Office building"
## [8] "5_Small retail space"
## [9] "7_Retail development with car parking"2.1.3 Test completeness: missing values per variable
## [,1]
## Source...1 0
## Business count 0
## Business within MOB 864
## Multiple buildings 870
## Multi-occupier building 930
## Source...6 339
## codex 13
## Join 79
## Xcoord 6
## Ycoord 10
## AAP 4
## Site allocation 165
## Sub-area 23
## Business name 1
## Street no 528
## Unit 758
## Floor 90
## Street 87
## 2015-2019 21
## Notes_on_C 892
## Business activity 158
## SIC CODE 68
## Sector 0
## Building use category 476
## Building type 5
## Actual number of employee 75
## Estimated number of employee 22
## TOTAL NUMBER OF EMPLOYEE 10
## employees for density 67
## GF multiplier 67
## UF multiplier 76
## B multiplier 77
## Long_surve 319
## GF Floorspace area 74
## UF Floorspace 113
## Total floorspace 73
## Total floorspace post VOA+15% analysis 81
## density 192
## 2.07 What % of employees of employees live locally? 798
## ...40 943
## ...41 942
## ...42 942
## ...43 942
## ...44 943
## ...45 943
## ...46 943
## ...47 9412.1.4 Plot (860 obs.)
2.2 Geopackage file
From file 164_OKR YARDSPACE BASE 191104.gpkg in WMT OKR Business Survey 2019.zip as yard
## Reading layer `164_OKR YARDSPACE BASE 191104' from data source `/Users/nicolas/Documents/SINDA_local/data_from_southwark/WMT OKR Business Survey 2019/164_OKR YARDSPACE BASE 191104.gpkg' using driver `GPKG'
## Simple feature collection with 608 features and 5 fields
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: 532501 ymin: 177190 xmax: 535390.9 ymax: 179254.2
## projected CRS: unnamed2.2.1 Check variables in bbase (6 variables)
## Classes 'sf' and 'data.frame': 608 obs. of 6 variables:
## $ SUB_AREA : chr "1" "1" "1" "1" ...
## $ SITE_ALLOC: chr "OKR3" "OKR3" "OKR3" "OKR3" ...
## $ TYPE : chr "1" "4" "1" "2.1" ...
## $ area : num 1935 1575 718 1198 4211 ...
## $ perimeter : num 208 317 173 163 457 ...
## $ geom :sfc_POLYGON of length 608; first list element: List of 1
## ..$ : num [1:12, 1:2] 533352 533363 533370 533376 533371 ...
## ..- attr(*, "class")= chr [1:3] "XY" "POLYGON" "sfg"
## - attr(*, "sf_column")= chr "geom"
## - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA
## ..- attr(*, "names")= chr [1:5] "SUB_AREA" "SITE_ALLOC" "TYPE" "area" ...2.2.2 Factor levels per variable describing type
## $SUB_AREA
## [1] "" "-" "1" "2" "2.2" "3" "4" "5" "6"
##
## $SITE_ALLOC
## [1] "" "OKR10" "okr11" "OKR11" "OKR12" "okr13" "OKR13" "OKR14" "OKR15"
## [10] "OKR16" "okr17" "OKR17" "OKR18" "OKR2" "OKR3" "OKR4" "OKR6" "OKR7"
## [19] "OKR8" "OKR9" "SPI." "SPIL1" "SPIL2"
##
## $TYPE
## [1] "" "1" "12" "2" "2.1" "2.2" "2.3" "21." "3"
## [10] "4" "5" "6" "OKR13"2.2.3 Test completeness: missing values per variable
## [,1]
## SUB_AREA 0
## SITE_ALLOC 0
## TYPE 0
## area 0
## perimeter 0